Upload
others
View
0
Download
0
Embed Size (px)
Citation preview
The global capital flows cycle: structural drivers and transmission channels
Global Research Forum on International Macroeconomics and Finance Frankfurt am Main, 29-30 November 2018
Maurizio M. Habib* (joint with F. Venditti) European Central Bank
* The views expressed are those of the authors and do not necessarily reflect those of the European Central Bank.
Rubric
www.ecb.europa.eu ©
• The global financial cycle: the debate
• Measuring global risk: the Global Stock Market Factor
• A structural interpretation of global risk
• Drivers of the global capital flows cycle
• The trilemma in the transmission of push factors to global capital flows
• Concluding remarks
2
Outline
Rubric
www.ecb.europa.eu ©
• The global financial cycle: the debate
• Measuring global risk: the Global Stock Market Factor
• A structural interpretation of global risk
• Drivers of the global capital flows cycle
• The trilemma in the transmission of push factors to global capital flows
• Concluding remarks
3
Outline
Rubric
www.ecb.europa.eu © 4
The global financial cycle: definition and policy relevance
Definition “There is a global financial cycle in capital flows, asset prices and in credit growth. This cycle comoves with the VIX, a measure of uncertainty and risk aversion of the markets”
Hélène Rey: Jackson Hole Symposium, August 2013 Policy relevance “U.S. monetary policy shocks are transmitted and affect financial conditions even in inflation-targeting economies with large financial markets… flexible exchange rates are not enough to guarantee monetary autonomy in a world of large capital flows” (dilemma not trilemma)
Hélène Rey: IMF Mundell-Fleming Lecture, November 2014
Rubric
www.ecb.europa.eu © 5
Global financial cycle: the evidence
• Global push factors, especially risk, associated with waves of capital flows (Forbes and Warnock, 2012) and “gatekeepers” of surges to EMEs (Ghosh et al. 2014)
• Risky asset prices: one global factor explains co-movement, reflecting risk appetite and realised volatility (Miranda-Agrippino and Rey, 2018)
• US monetary policy, USD and leverage of international banks driving cross-border banking flows (Bruno and Shin, 2015)
• Common fluctuations in prices of risky assets increased beyond real sector integration (Jorda et al. 2017)
Critical views • Global financial cycle not important; global factor explains at most
25 percent of the variation of capital flows (Cerutti et al., 2017)
• A common component accounts for about 20 to 40 percent of the variation in countries’ domestic FCIs (Arregui et al., 2018)
Rubric
www.ecb.europa.eu © 6
Global financial cycle: the policy dimension
The trilemma • Floating exchange rates allow for a higher degree of monetary
policy autonomy (Obstfeld, Shambaugh and Taylor, 2005); possibly only when Fed tightens monetary policy (“fear of appreciation” of Han and Wei, 2018)
• Transmission of global financial shocks to credit, house prices, leverage and output stronger in EMEs with pegs (Obstfeld, Ostry and Qureshi, 2018)
The dilemma • Even with a floating exchange rate, a country may lose control of
domestic financial conditions (Rey, 2013 and 2016)
• Rigid FX regimes not associated with higher sensitivity of stock markets or domestic credit to global factors (Passari and Rey, 2015)
Rubric
www.ecb.europa.eu © 7
Our contribution
On the co-movement of capital flows Rich interpretation of the structural drivers of global risk:
– financial shocks matter more than US monetary policy shocks in driving global risk
– global risk is tightly associated with global capital flows
On the policy dimension – A fixed exchange rate increases the transmission of global risk
to capital flows (in particular “other investment”, i.e. bank lending) – For EMEs with open capital account and an exchange rate target,
impact of global risk shocks is economically meaningful
Rubric
www.ecb.europa.eu ©
• The global financial cycle: the debate
• Measuring global risk: the Global Stock Market Factor
• A structural interpretation of global risk
• Drivers of the global capital flows cycle
• The trilemma in the transmission of push factors to global capital flows
• Concluding remarks
8
Outline
Rubric
www.ecb.europa.eu ©
• Global factor similar to Miranda-Agrippino and Rey (MAR)
• Dataset consists of stock market returns for 60 countries
• Our dataset more “global” than MAR (43% of their series US based)
• Simple dynamic factor model: 𝑠𝑠𝑖𝑖,𝑡𝑡 is the log-change in stock
market index in country“i”
9
Global Stock Market Factor: our version of the MAR indicator
𝑠𝑠𝑖𝑖,𝑡𝑡 = 𝛽𝛽𝑔𝑔𝑓𝑓𝑔𝑔,𝑡𝑡 + �𝛽𝛽𝑙𝑙𝑓𝑓𝑙𝑙,𝑡𝑡 + 𝜀𝜀𝑖𝑖,𝑡𝑡
𝑟𝑟
𝑙𝑙=1
𝐹𝐹𝑡𝑡= A(L) 𝐹𝐹𝑡𝑡−1 + ϵ𝑡𝑡,
where 𝐹𝐹𝑡𝑡=[𝑓𝑓𝑔𝑔,𝑡𝑡, 𝑓𝑓1,𝑡𝑡,…,𝑓𝑓𝑝𝑝,𝑡𝑡]
• Our Global Stock Market Factor is the cumulated value of 𝑓𝑓𝑔𝑔,𝑡𝑡
Rubric
www.ecb.europa.eu © 10
Correlation between our GRA indicator and other indicators
Rubric
www.ecb.europa.eu ©
• The global financial cycle: the debate
• Measuring global risk: the Global Stock Market Factor
• A structural interpretation of global risk
• Drivers of the global capital flows cycle
• The trilemma in the transmission of push factors to global capital flows
• Concluding remarks
11
Outline
Rubric
www.ecb.europa.eu ©
Factor Augmented Vector Auto Regression (FAVAR) including US and global variables:
1. 1-Year Treasury Constant Maturity Rate
2. S&P 500 Index (log)
3. US Consumer Price Index (log)
4. High-Yield USD Corporate Bond Index (yield)
5. Trade Weighted US Dollar index (log)
6. Oil Price (Brent Quality, log)
7. Global Stock Market Factor
Monthly data, 1990M2 – 2018M5, 6 lags, estimated via Bayesian Methods (Minnesota Priors and conventional prior setting)
12
A structural interpretation of global risk
Rubric
www.ecb.europa.eu ©
A rich configuration of (four) shocks – (1) US Monetary Policy shock identified via External Instrument:
monetary policy surprises as in Jarocinski and Karadi (2018) – (2) US Demand, (3) Financial and (4) Geopolitical Uncertainty
shocks through Sign Restrictions
13
The identification scheme
ShockMonetary Policy
(signs implied by external instrument)
US Demand Financial Geopolitical Uncertainty
US Treasury Rate (one-year) + - - -SP500 (log) - - - -US Consumer Price Index (log) - - - +High Yield USD Corporate Bonds (yield) + - +Trade Weighted US Dollar index (log) + - + +Oil Price (Brent Quality, log) - - +Global Stock Market Factor + + + +
Rubric
www.ecb.europa.eu © 14
Forecast Error Variance Decomposition: Global Stock Market Factor
• Significant impact of US monetary policy on global risk appetite
• Yet, overall relevance of “financial shocks” much larger
• Role of US demand shocks negligible
Shock15th
percentile mean 85th percentile
US monetary policy 0.11 0.19 0.28
Financial 0.00 0.23 0.68
Geopolitical uncertainty 0.01 0.07 0.13
US demand 0.01 0.13 0.26
Rubric
www.ecb.europa.eu ©
• The global financial cycle: the debate
• Measuring global risk: the Global Stock Market Factor
• A structural interpretation of global risk
• Drivers of the global capital flows cycle
• The trilemma in the transmission of push factors to global capital flows
• Concluding remarks
15
Outline
Rubric
www.ecb.europa.eu © 16
Capital flows significantly correlated with global risk
Sources: IMF BPS and authors’ calculations. Notes: Capital flows are total “gross capital inflows” aggregated over 50 economies and reported as a percentage of total GDP (left-hand scale). The Global Stock Market Factor is constructed from a dynamic factor model for stock returns in 63 countries (right-hand scale, inverted).
Capital flows and Global Stock Market Factor since 1990s
-4.0
-3.0
-2.0
-1.0
0.0
1.0
2.0
3.0-10
0
10
20
30
40
50
1990 1993 1996 1999 2002 2005 2008 2011 2014 2017
Total Capital Flows (% of GDP)
Global Stock Market Factor (rhs, inverted scale)
Correlation: -0.74
Rubric
www.ecb.europa.eu © 17
Push factors and capital flows
Panel regression for 50 advanced and emerging economies (excluding small financial centres) between 1990 and 2017 (quarterly)
Pull factors: domestic inflation and real GDP growth
Push factors: world GDP growth, global risk, US monetary policy
Global risk: Global Stock Market Factor (GSMF)
US monetary policy: effective Fed funds rate (level or change), monetary policy surprises (Gertler-Karadi) or monetary policy uncertainty (Bloom)
Rubric
www.ecb.europa.eu ©
Mean SD Min Max Obs.
Gross capital inflows:Direct investment (% of GDP) 3.0 6.2 -52.1 231.3 5,251Portfolio equity (% of GDP) 0.5 2.0 -26.6 29.3 4,998Portfolio debt (% of GDP) 1.9 5.2 -47.4 39.6 5,017Other investment (% of GDP) 2.4 10.9 -124.8 205.5 5,212Total (% of GDP) 7.8 13.8 -113.6 229.4 5,163
Push factors:Global Stock Market Factor 0.0 1.0 -2.5 1.6 5,600VIX 19.4 7.3 10.3 58.7 5,600US Fed funds rate & Wu-Xia shadow rate (%) 2.9 3.1 -2.9 9.7 5,800Bloom US monetary policy uncertainty (index) 88.9 58.0 16.6 407.9 5,750Gertler-Karadi US monetary policy surprise (%) 0.0 0.5 -1.2 2.0 5,600World GDP growth, annualised (%) 3.4 1.3 -1.8 5.7 5,800
Policy and control variables:Chinn-Ito capital account liberalisation (index) 0.68 0.34 0.00 1.00 5,528External liabilities (ratio to GDP) 1.14 0.91 0.09 6.69 5,516US exposure to domestic equity and debt (% of GDP) 32.1 39.0 0.0 263.6 4,690Strict peg, Obstfeld, Shambaugh and Taylor (dummy) 0.30 0.46 0.00 1.00 5,800Soft peg, Obstfeld, Shambaugh and Taylor (dummy) 0.30 0.46 0.00 1.00 5,684Strict peg, Ilzetzki, Reinhart and Rogoff (dummy) 0.30 0.46 0.00 1.00 5,800Soft peg, Ilzetzki, Reinhart and Rogoff (dummy) 0.56 0.50 0.00 1.00 5,800Inflation, year-on-year (%) 10.4 33.2 -3.82 495.2 5,325Domestic GDP growth, year-on-year (%) 3.2 4.8 -19.7 73.0 5,261
18
Data: summary statistics
Outliers in capital flows winsorise data (1% cut)
Rubric
www.ecb.europa.eu ©
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Dependent variable Direct investm.
Portfolio equity
Portfolio debt
Other investm. Total Direct
investm.Portfolio equity
Portfolio debt
Other investm. Total
Inflation -0.003* 0.001 0.002 0.003 0.003 -0.003** 0.001 0.001 0.007 0.005(0.001) (0.001) (0.003) (0.004) (0.004) (0.001) (0.001) (0.003) (0.004) (0.004)
Domestic GDP growth 0.029* 0.009* 0.002 0.117** 0.172** 0.028* 0.009* 0.000 0.122** 0.175**(0.015) (0.005) (0.020) (0.048) (0.066) (0.015) (0.005) (0.021) (0.050) (0.068)
World GDP growth 0.078** -0.030 -0.046 0.605*** 0.634** 0.075** -0.050 -0.033 0.572*** 0.574**(0.039) (0.048) (0.125) (0.122) (0.288) (0.035) (0.044) (0.139) (0.131) (0.274)
Global Stock Market Factor -0.485*** -0.121* -0.342** -0.477** -1.347*** -0.471*** -0.117** -0.271** -0.668*** -1.448***(0.058) (0.072) (0.133) (0.238) (0.345) (0.060) (0.048) (0.128) (0.240) (0.318)
US policy rate (level) -0.010 -0.008 -0.046 0.137* 0.063(0.015) (0.016) (0.045) (0.070) (0.087)
US policy rate (change) 0.051 0.159 -0.011 -0.017 0.322(0.095) (0.113) (0.337) (0.382) (0.674)
Observations 4,835 4,584 4,595 4,804 4,753 4,835 4,584 4,595 4,804 4,753Countries 50 49 49 50 50 50 49 49 50 50R2 0.182 0.0776 0.116 0.122 0.215 0.182 0.0795 0.116 0.121 0.215
19
Capital flows and global risk: a robust relationship (1)
Notes: The model includes country-specific fixed effects and four lags of the dependent variable. Driscoll-Kraay standard errors, accounting for cross-sectional and temporal dependence of the residuals, are reported in parentheses. The asterisks ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively.
Panel: capital flows, Global Stock Market Factor and US monetary policy
Rubric
www.ecb.europa.eu ©
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Dependent variable Direct investm.
Portfolio equity
Portfolio debt
Other investm. Total Direct
investm.Portfolio equity
Portfolio debt
Other investm. Total
Inflation -0.003** 0.001 0.001 0.007* 0.005 -0.003** 0.001 0.001 0.007 0.005(0.001) (0.001) (0.003) (0.004) (0.004) (0.001) (0.001) (0.003) (0.004) (0.004)
Domestic GDP growth 0.028* 0.010* 0.002 0.123** 0.177** 0.028* 0.010* 0.002 0.121** 0.176**(0.015) (0.005) (0.021) (0.051) (0.068) (0.015) (0.005) (0.021) (0.050) (0.069)
World GDP growth 0.081** -0.031 -0.043 0.566*** 0.603** 0.081** -0.049 -0.066 0.585*** 0.582**(0.039) (0.045) (0.123) (0.123) (0.269) (0.036) (0.037) (0.114) (0.128) (0.262)
Global Stock Market Factor -0.468*** -0.120** -0.296** -0.681*** -1.473*** -0.469*** -0.100* -0.257** -0.679*** -1.411***(0.061) (0.057) (0.133) (0.239) (0.308) (0.061) (0.051) (0.117) (0.232) (0.299)
0.031 -0.195*** -0.494* -0.257 -1.126*(0.086) (0.068) (0.263) (0.374) (0.612)
-0.000 -0.003*** -0.004 0.002 -0.005(0.001) (0.001) (0.003) (0.003) (0.006)
Observations 4,835 4,584 4,595 4,804 4,753 4,835 4,584 4,595 4,804 4,753Countries 50 49 49 50 50 50 49 49 50 50R2 0.182 0.0821 0.119 0.121 0.218 0.182 0.0908 0.119 0.121 0.215
US monetary policy surprises, Gertler-Karadi
US monetary policy uncertainty, Bloom
20
Capital flows and global risk: a robust relationship (2)
Notes: The model includes country-specific fixed effects and four lags of the dependent variable. Driscoll-Kraay standard errors, accounting for cross-sectional and temporal dependence of the residuals, are reported in parentheses. The asterisks ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively.
Panel: capital flows, Global Stock Market Factor and US monetary policy
Rubric
www.ecb.europa.eu © 21
Capital flows and global risk: robust to different samples
Notes: The model includes country-specific fixed effects, additional controls and four lags of the dependent variable. The asterisks ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively.
Advanced vs. emerging economies
Excluding financial centres and the global financial crisis in 2008-09
Sample
Dependent variable Direct investm.
Portfolio equity
Portfolio debt
Other investm. Total Direct
investm.Portfolio equity
Portfolio debt
Other investm. Total
Global Stock Market Factor -0.610*** -0.195** -0.708*** -1.048*** -2.477*** -0.388*** -0.062 0.036 -0.469* -0.854**(0.101) (0.095) (0.230) (0.337) (0.461) (0.066) (0.044) (0.102) (0.250) (0.338)
US monetary policy surprises -0.010 -0.158* -0.696** -0.116 -1.281 0.027 -0.208*** -0.386 -0.375 -0.984**(0.132) (0.084) (0.333) (0.654) (0.957) (0.077) (0.067) (0.287) (0.303) (0.475)
Observations 1,884 1,790 1,842 1,884 1,883 2,951 2,794 2,753 2,920 2,870Countries 18 18 18 18 18 32 31 31 32 32R2 0.117 0.0802 0.174 0.102 0.212 0.242 0.108 0.0509 0.217 0.269
Advanced economies Emerging economies
Sample
Dependent variable Direct investm.
Portfolio equity
Portfolio debt
Other investm. Total Direct
investm.Portfolio equity
Portfolio debt
Other investm. Total
Global Stock Market Factor -0.451*** -0.108* -0.284** -0.676*** -1.416*** -0.486*** -0.140*** -0.214 -0.581** -1.312***(0.056) (0.064) (0.127) (0.247) (0.308) (0.064) (0.034) (0.130) (0.239) (0.276)
US monetary policy surprises 0.014 -0.216*** -0.511* 0.051 -0.805 -0.039 -0.168** -0.238 0.135 -0.398(0.081) (0.077) (0.273) (0.332) (0.572) (0.075) (0.083) (0.188) (0.318) (0.388)
Observations 4,551 4,300 4,311 4,520 4,469 4,435 4,192 4,207 4,404 4,357Countries 47 46 46 47 47 50 49 49 50 50R2 0.193 0.0882 0.113 0.126 0.234 0.181 0.0818 0.126 0.116 0.224
Excluding large financial centres (US, UK, CH) Excluding global financial crisis (2008-09)
Rubric
www.ecb.europa.eu ©
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Driver
Dependent variable Direct investm.
Portfolio equity
Portfolio debt
Other investm. Total Direct
investm.Portfolio equity
Portfolio debt
Other investm. Total
Monetary policy shock -0.141 -0.203*** -0.439** -0.291 -1.164*** -0.445** -0.043 -0.321 -0.923** -1.663**(0.105) (0.066) (0.168) (0.360) (0.387) (0.206) (0.168) (0.325) (0.463) (0.711)
Financial shock -0.198 -0.308*** -1.200*** -1.081*** -2.810*** -0.632*** -0.034 -0.548** -1.456*** -2.447***(0.211) (0.054) (0.221) (0.346) (0.472) (0.166) (0.131) (0.274) (0.393) (0.574)
Geopolitical-uncertainty shock -0.203* -0.336*** -0.091 0.742** 0.254 -0.871** -0.507*** -0.584 -0.906 -2.866(0.110) (0.069) (0.217) (0.296) (0.397) (0.376) (0.173) (0.756) (1.256) (2.142)
Observations 4,835 4,584 4,595 4,804 4,753 4,835 4,584 4,595 4,804 4,753Countries 50 49 49 50 50 50 49 49 50 50R2 0.169 0.101 0.129 0.120 0.218 0.178 0.0790 0.117 0.122 0.215
Shocks Contributions
22
Unpacking the drivers of global risk and capital flows
Notes: The model includes country-specific fixed effects, four lags of the dependent variable and a vector of domestic (inflation and GDP growth) and global (GDP growth) control variables that can affect capital flows (omitted for space reasons). Driscoll-Kraay standard errors, accounting for cross-sectional and temporal dependence of the residuals, are reported in parentheses. The asterisks ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively.
Panel: capital flows and structural drivers of Global Stock Market Factor
Rubric
www.ecb.europa.eu ©
• The global financial cycle: the debate
• Measuring global risk: the Global Stock Market Factor
• A structural interpretation of global risk
• Drivers of the global capital flows cycle
• The trilemma in the transmission of push factors to global capital flows
• Concluding remarks
23
Outline
Rubric
www.ecb.europa.eu © 24
Transmission of risk to capital flows: testing the policy trilemma Similarly to Passari and Rey (2015) and Obstfeld et al. (2018)
Policy vector (z): De jure capital account openness index (KO) and dummies for fixed and intermediate exchange rate regime (D)
Push factor vector (p): Global Stock Market Factor (GSMF) and US monetary policy surprises (MPS)
Excluding currency, banking and sovereign debt crises, when exchange rate regime more likely to change
Rubric
www.ecb.europa.eu ©
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Exchange rate regime classification
Dependent variable Direct investm.
Portfolio equity
Portfolio debt
Other investm. Total Direct
investm.Portfolio equity
Portfolio debt
Other investm. Total
Global Stock Market Factor (GSMF) -0.124 -0.125 0.076 1.008*** 0.841** 0.205 -0.279** -0.088 1.369*** 1.136***(0.111) (0.094) (0.166) (0.263) (0.326) (0.133) (0.134) (0.197) (0.328) (0.423)
GSMF * KAOPEN -0.366** -0.001 -0.524** -1.772*** -2.717*** -0.480*** 0.055 -0.409* -1.966*** -2.765***(0.150) (0.093) (0.225) (0.374) (0.495) (0.151) (0.115) (0.210) (0.394) (0.485)
GSMF * Strict peg -0.300*** -0.072 -0.024 -1.348*** -1.768*** -0.482*** 0.018 -0.091 -1.377*** -2.039***(0.096) (0.047) (0.265) (0.320) (0.391) (0.131) (0.076) (0.326) (0.482) (0.547)
GSMF * Soft peg -0.067 0.024 0.027 -0.357 -0.245 -0.359*** 0.159* 0.178 -0.498** -0.426(0.095) (0.088) (0.122) (0.261) (0.328) (0.099) (0.083) (0.154) (0.203) (0.320)
US Monetary Policy Shock (MPS) -0.017 -0.149 -0.611* -0.429 -1.029 -0.095 -0.036 -0.263 -0.967 -1.042(0.143) (0.168) (0.345) (0.427) (0.750) (0.170) (0.138) (0.398) (0.640) (0.852)
MPS * KAOPEN 0.089 0.013 -0.428 -0.123 -0.951 0.081 -0.026 -0.329 0.005 -0.711(0.274) (0.166) (0.375) (0.643) (0.839) (0.277) (0.168) (0.383) (0.693) (0.890)
MPS * Strict peg -0.003 -0.221** 0.858 1.383** 1.860* 0.094 -0.256** 0.315 1.932** 1.788*(0.169) (0.101) (0.616) (0.582) (0.955) (0.186) (0.114) (0.533) (0.740) (0.935)
MPS * Soft peg -0.046 -0.031 0.503* 0.355 1.073 0.084 -0.143 -0.236 0.639 0.238(0.161) (0.104) (0.300) (0.560) (0.799) (0.123) (0.120) (0.245) (0.471) (0.587)
Observations 4,374 4,179 4,187 4,343 4,324 4,374 4,179 4,187 4,343 4,324Countries 50 49 49 50 50 50 49 49 50 50R2 0.167 0.0858 0.118 0.146 0.238 0.168 0.0887 0.118 0.146 0.238
Obstfeld, Shambaugh and Taylor Ilzetzki, Reinhart and Rogoff
25
Trilemma in the transmission of global risk to capital flows
Using de jure measure of capital account openness: Chinn-Ito index (KAOPEN)
Notes: The model includes country-specific fixed effects, four lags of the dependent variable and a vector of domestic (inflation and GDP growth) and global (GDP growth) control variables that can affect capital flows (omitted for space reasons). Driscoll-Kraay standard errors, accounting for cross-sectional and temporal dependence of the residuals, are reported in parentheses. The asterisks ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively.
Rubric
www.ecb.europa.eu © 26
The trilemma in the transmission of global risk to capital flows
Using de facto measure of financial openness (FINOPEN): Total external liabilities as a ratio to GDP
Notes: The model includes country-specific fixed effects, four lags of the dependent variable and a vector of domestic (inflation and GDP growth) and global (GDP growth) control variables that can affect capital flows (omitted for space reasons). Driscoll-Kraay standard errors, accounting for cross-sectional and temporal dependence of the residuals, are reported in parentheses. The asterisks ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively.
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Exchange rate regime classification
Dependent variable Direct investm.
Portfolio equity
Portfolio debt
Other investm. Total Direct
investm.Portfolio equity
Portfolio debt
Other investm. Total
US monetary policy surprise 0.023 -0.195** -0.513** -0.018 -0.795* 0.024 -0.194** -0.503** -0.021 -0.781*(0.093) (0.076) (0.235) (0.287) (0.441) (0.093) (0.076) (0.236) (0.289) (0.441)
Global Stock Market Factor (GSMF) -0.175* -0.172** -0.006 0.679 0.280 -0.001 -0.287*** -0.189 0.578* 0.030(0.089) (0.076) (0.193) (0.415) (0.465) (0.095) (0.086) (0.191) (0.337) (0.448)
GSMF * FINOPEN -0.189** 0.049 -0.244 -0.802** -1.214*** -0.186** 0.053 -0.239 -0.820** -1.207***(0.091) (0.039) (0.190) (0.371) (0.427) (0.093) (0.042) (0.187) (0.387) (0.444)
GSMF * Strict peg -0.312*** -0.073 -0.062 -1.414*** -1.915*** -0.452*** 0.021 -0.027 -1.150** -1.742***(0.110) (0.057) (0.240) (0.317) (0.388) (0.141) (0.082) (0.287) (0.515) (0.538)
GSMF * Soft peg -0.059 0.017 0.024 -0.323 -0.209 -0.256*** 0.148** 0.278 -0.074 0.191(0.110) (0.089) (0.137) (0.229) (0.324) (0.087) (0.071) (0.186) (0.234) (0.336)
Observations 4,395 4,199 4,207 4,359 4,346 4,395 4,199 4,207 4,359 4,346Countries 50 49 49 50 50 50 49 49 50 50R2 0.173 0.0869 0.118 0.147 0.238 0.174 0.0898 0.119 0.146 0.239
Obstfeld, Shambaugh and Taylor Ilzetzki, Reinhart and Rogoff
Rubric
www.ecb.europa.eu ©
(1) (2) (3) (4) (5) (6) (7) (8)
Benchmark Advanced economies
Emerging economies
Excl. euro area
Excl. financial centres
Excl. global fin. crisis
Including crises
Including time
dummies
De jure capital account openness (KAOPEN) 0.799 4.531 0.439 0.280 0.538 -0.205 0.747 0.854(0.855) (3.169) (0.868) (0.836) (0.807) (0.813) (0.952) (0.731)
Strict peg, OST 0.776 0.639 0.933 0.485 0.985* 0.644 1.173** 0.561(0.663) (1.679) (0.704) (0.662) (0.568) (0.533) (0.590) (0.534)
Soft peg, OST 0.056 0.448 0.073 0.108 -0.058 -0.154 0.201 -0.053(0.480) (1.251) (0.312) (0.448) (0.362) (0.343) (0.425) (0.381)
US monetary policy surprise -0.917* -0.872 -0.967* -1.039** -0.586 -0.332 -1.051*(0.504) (0.765) (0.500) (0.464) (0.473) (0.430) (0.607)
Global Stock Market Factor (GSMF) 0.846** 3.907 0.491** 0.936*** 0.642** 0.824** 0.847***(0.332) (2.548) (0.230) (0.322) (0.277) (0.386) (0.298)
GSMF * KAOPEN -2.667*** -5.472** -2.497*** -2.572*** -2.488*** -2.495*** -2.625*** -2.320***(0.495) (2.702) (0.607) (0.475) (0.436) (0.515) (0.493) (0.621)
GSMF * Strict peg, OST -1.858*** -1.991** -1.619*** -1.794*** -1.735*** -1.832*** -1.926*** -1.702***(0.396) (0.772) (0.470) (0.439) (0.399) (0.436) (0.388) (0.511)
GSMF * Soft peg, OST -0.283 -1.724** 0.358 -0.293 0.061 -0.214 -0.265 -0.243(0.324) (0.729) (0.288) (0.335) (0.256) (0.335) (0.325) (0.381)
Observations 4,324 1,783 2,541 3,696 4,056 4,088 4,696 4,324Countries 50 18 32 50 47 50 50 50R2 0.236 0.206 0.317 0.218 0.259 0.239 0.235 0.292
27
Trilemma in the transmission of global risk to capital flows: robustness
Dependent variable: Total capital flows Policy controls: Chinn-Ito de jure index of capital account liberalisation (KAOPEN) and Obstfeld, Shambaugh and Taylor (OST) exchange rate regime classification
Notes: The dependent variable is “Total capital inflows””. The model includes country-specific fixed effects, four lags of the dependent variable and a vector of domestic (inflation and GDP growth) and global (GDP growth) control variables that can affect capital flows (omitted for space reasons). The asterisks ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively.
Rubric
www.ecb.europa.eu © 28
Economic significance of the impact of risk on capital flows
Impact of one standard-deviation change in Global Stock Market Factor on capital flows (absolute value, % of GDP)
Notes: numbers in italics refer to the sample mean and sample standard deviation. Benchmark model including US monetary policy surprises. Policy controls: Chinn-Ito de jure index of capital account liberalisation and Obsfeld, Shambaugh, Taylor (2010) exchange rate regime classification. * Fully open economies correspond to observations for which the (normalised) Chinn-Ito index takes the value of 1.
Direct investment
Other investment Total
Full sample Average impact 0.5 0.7 1.5Fully open economies* 0.6 1.4 2.5Open and strict peg 0.7 2.1 3.7Sample Mean 3.0 2.4 7.8Standard Deviation (6.2) (10.9) (13.8)
Advanced economies Average impact 0.6 1.0 2.5Fully open economies* 1.4 1.2 2.8Fully open and strict peg 1.2 1.5 3.6Sample Mean 2.4 3.4 9.6Standard Deviation (5.1) (15.0) (17.4)
Emerging markets Average impact 0.4 0.5 0.9Fully open economies* 0.6 1.4 2.1Fully open and strict peg 0.8 2.5 3.6Sample Mean 3.4 1.8 6.6Standard Deviation (6.7) (6.9) (10.6)
Rubric
www.ecb.europa.eu ©
• The global financial cycle: the debate
• Measuring global risk: the Global Stock Market Factor
• A structural interpretation of global risk
• Drivers of the global capital flows cycle
• The trilemma in the transmission of push factors to global capital flows
• Concluding remarks
29
Outline
Rubric
www.ecb.europa.eu © 30
Concluding remarks
The drivers of global risk and capital flows
1. Global capital flows cycle is closely connected to global risk
2. In turn, global risk is largely driven by US monetary policy shocks and financial shocks
3. Yet, financial shocks matter more than US monetary policy shocks
The transmission of global risk to capital flows
4. There is a trilemma in the global capital flows cycle
5. Strict pegs increase the transmission of global risk to capital flows
6. This is largely driven by “other investment”, i.e. bank lending
7. Trilemma is economically relevant for EMEs
Rubric
www.ecb.europa.eu © 31
Background slides
Rubric
www.ecb.europa.eu © 32
Data
Variable Source
Gross capital inflows IMF Balance of Payments Statistics (BPS)
Stock market indices Global Financial Data
VIX, US effective Fed funds rate, Wu-Xia US shadow rate
Haver
US monetary policy surprises Gertler and Karadi (2015)
US monetary policy uncertainty Baker, Bloom and Davis (2016) at www.PolicyUncertainty.com
Inflation and GDP growth Haver
De jure capital account liberalisation Chinn and Ito (2006)
External liabilities External Wealth of Nations Mark II dataset and IMF BPS
Bilateral US portfolio investment US Treasury International Capital (TIC) System
Exchange rate regime classification Obstfeld, Shambaugh and Taylor (2010) and Ilzetzki, Reinhart, and Rogoff (2017)
Rubric
www.ecb.europa.eu © 33
Data: summary statistics, advanced vs. emerging economies
Mean SD Min Max Obs. Mean SD Min Max Obs.
Gross capital inflows:Direct investment (% of GDP) 2.4 5.1 -31.5 94.5 2,036 3.4 6.7 -52.1 231.3 3,215Portfolio equity (% of GDP) 0.8 2.5 -17.0 29.3 1,946 0.4 1.5 -26.6 17.2 3,052Portfolio debt (% of GDP) 3.0 6.5 -47.4 39.6 2,002 1.1 3.8 -23.9 38.5 3,015Other investment (% of GDP) 3.4 15.0 -124.8 205.5 2,036 1.8 6.9 -47.9 85.9 3,176Total (% of GDP) 9.6 17.4 -113.6 214.0 2,035 6.6 10.6 -57.1 229.4 3,128
Push factors:Global Stock Market Factor 0.0 1.0 -2.5 1.6 2,016 0.0 1.0 -2.5 1.6 3,584VIX 19.4 7.3 10.3 58.7 2,016 19.4 7.3 10.3 58.7 3,584US Fed funds rate & Wu-Xia shadow rate (%) 2.9 3.1 -2.9 9.7 2,088 2.9 3.1 -2.9 9.7 3,712Bloom US monetary policy uncertainty (index) 88.9 58.0 16.6 407.9 2,070 88.9 58.0 16.6 407.9 3,680Gertler-Karadi US monetary policy surprise (%) 0.0 0.5 -1.2 2.0 2,016 0.0 0.5 -1.2 2.0 3,584World GDP growth, annualised (%) 3.4 1.3 -1.8 5.7 2,088 3.4 1.3 -1.8 5.7 3,712
Policy and control variables:Chinn-Ito capital account liberalisation (index) 0.94 0.15 0.17 1.00 2,060 0.53 0.34 0.00 1.00 3,468External liabilities (ratio to GDP) 1.71 1.15 0.32 6.69 2,080 0.79 0.45 0.09 3.81 3,436US exposure to domestic equity and debt (% of GDP) 56.5 51.5 2.3 263.6 1,632 19.2 20.8 0.00 137.1 3,058Strict peg, Obstfeld, Shambaugh and Taylor (dummy) 0.39 0.49 0.00 1.00 2,088 0.25 0.43 0.00 1.00 3,712Soft peg, Obstfeld, Shambaugh and Taylor (dummy) 0.28 0.45 0.00 1.00 2,088 0.31 0.46 0.00 1.00 3,596Strict peg, Ilzetzki, Reinhart and Rogoff (dummy) 0.42 0.49 0.00 1.00 2,088 0.23 0.42 0.00 1.00 3,712Soft peg, Ilzetzki, Reinhart and Rogoff (dummy) 0.37 0.48 0.00 1.00 2,088 0.66 0.47 0.00 1.00 3,712Inflation, year-on-year (%) 2.26 2.24 -2.41 21.0 1,944 15.1 41.0 -3.82 495.2 3,381Domestic GDP growth, year-on-year (%) 1.8 2.4 -10.9 8.7 1,944 4.1 5.6 -19.7 73.0 3,317
Advanced economies Emerging economies
Rubric
www.ecb.europa.eu © 34
Historical comparison, GSMF vs other indicators – Global Stock Market Factor (GSMF), lhs – alternative indicator, rhs
Notes: grey shaded areas indicate US recessions.
Rubric
www.ecb.europa.eu © 35
Impulse Response Functions
Rubric
www.ecb.europa.eu © 36
Historical Contributions: Global Stock Market Factor – Global Stock Market Factor, lhs – Contribution of shock, rhs
Rubric
www.ecb.europa.eu © 37
Correlation of capital flows, global risk and US policy rate
Sources: IMF, Haver Analytics and authors’ calculations. Notes: Capital flow liabilities as a percentage of GDP. US policy rate refers to the effective federal funds rate extended with the Wu-Xia shadow rate. Nominal USD appreciation is calculated as the log change in the nominal effective exchange rate (NEER). * Asterisk indicates statistical significance at the 5% level.
Correlation of capital inflows, global risk and US policy rate: 1990 – 2017 (quarterly data)
Capital flows - Advanced
Capital flows - Emerging VIX Global Stock
Market Factor US policy
rate
Capital flows - Advanced 1
Capital flows - Emerging 0.59* 1
VIX -0.27* -0.34* 1
Global Stock Market Factor -0.61* -0.51* 0.09 1
US policy rate 0.11 -0.15 0.02 -0.35* 1
Rubric
www.ecb.europa.eu © 38
Capital flows and VIX: less robust relationship
Notes: The model includes country-specific fixed effects, four lags of the dependent variable and a vector of domestic (inflation and GDP growth) and global (GDP growth) control variables that can affect capital flows (omitted for space reasons). Driscoll-Kraay standard errors, accounting for cross-sectional and temporal dependence of the residuals, are reported in parentheses. The asterisks ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively.
Panel: capital flows, VIX and US monetary policy
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) 11 12 13 14 15 (16) (17) (18) (19) (20)Dependent variable DI PE PD OI TOT DI PE PD OI TOT DI PE PD OI TOT DI PE PD OI TOT
VIX 0.013 -0.019*** -0.055** -0.027 -0.104* 0.016 -0.018*** -0.062*** -0.029 -0.105 0.014 -0.016** -0.048** -0.021 -0.083 0.017 -0.011** -0.046* -0.030 -0.089(0.011) (0.005) (0.024) (0.034) (0.058) (0.012) (0.006) (0.023) (0.042) (0.064) (0.013) (0.006) (0.024) (0.037) (0.059) (0.011) (0.006) (0.024) (0.038) (0.065)
US policy rate (level) 0.061** 0.015 0.018 0.210*** 0.261***(0.029) (0.014) (0.046) (0.071) (0.098)
US policy rate (change) 0.071 0.051 -0.348 -0.253 -0.286(0.128) (0.115) (0.295) (0.471) (0.608)
0.030 -0.120* -0.288 -0.101 -0.751(0.102) (0.067) (0.207) (0.330) (0.515)
-0.001 -0.003*** -0.003 0.002 -0.004(0.001) (0.001) (0.002) (0.003) (0.005)
Observations 4,835 4,584 4,595 4,804 4,753 4,835 4,584 4,595 4,804 4,753 4,835 4,584 4,595 4,804 4,753 4,835 4,584 4,595 4,804 4,753Countries 50 49 49 50 50 50 49 49 50 50 50 49 49 50 50 50 49 49 50 50R2 0.171 0.0804 0.119 0.121 0.210 0.168 0.0798 0.120 0.116 0.205 0.168 0.0813 0.120 0.116 0.207 0.168 0.0895 0.120 0.116 0.206
US monetary policy surprises, GK
US monetary policy uncertainty, Bloom
Rubric
www.ecb.europa.eu ©
(1) (2) (3) (4) (5) (6) (7) (8)
Benchmark Advanced economies
Emerging economies
Excl. euro area
Excl. financial centres
Excl. global fin. crisis
Including crises
Including time
dummies
De jure capital account openness (KAOPEN) 0.544 6.214* 0.091 -0.349 0.354 -0.413 0.595 0.521(0.893) (3.514) (0.831) (0.842) (0.822) (0.821) (0.973) (0.784)
Strict peg, IRR 3.407*** 3.714** 3.371*** 5.089*** 2.317*** 3.191*** 3.309*** 3.528**(0.957) (1.664) (1.149) (1.367) (0.876) (1.005) (0.732) (1.643)
Soft peg, IRR 2.698*** 5.523** 1.581** 3.830*** 1.131 2.702** 2.493*** 2.565*(0.975) (2.283) (0.697) (1.147) (0.688) (1.040) (0.865) (1.440)
US monetary policy surprise -0.917* -0.886 -0.946* -1.011** -0.589 -0.330 -1.077*(0.507) (0.760) (0.502) (0.465) (0.471) (0.426) (0.611)
Global Stock Market Factor (GSMF) 1.124** 3.966 0.180 1.302*** 1.138*** 1.196** 1.105**(0.430) (2.554) (0.629) (0.384) (0.352) (0.486) (0.430)
GSMF * KAOPEN -2.688*** -5.609** -2.437*** -2.789*** -2.389*** -2.544*** -2.629*** -2.197***(0.481) (2.652) (0.554) (0.466) (0.391) (0.516) (0.479) (0.647)
GSMF * Strict peg, IRR -2.140*** -2.156** -1.355 -2.034*** -2.282*** -2.213*** -2.187*** -1.798**(0.564) (0.852) (0.894) (0.623) (0.581) (0.634) (0.522) (0.686)
GSMF * Soft peg, IRR -0.438 -0.735 0.353 -0.473 -0.630* -0.493 -0.432 -0.070(0.324) (0.499) (0.718) (0.325) (0.330) (0.361) (0.347) (0.598)
Observations 4,324 1,783 2,541 3,696 4,056 4,088 4,696 4,324Countries 50 18 32 50 47 50 50 50R2 0.237 0.209 0.316 0.220 0.259 0.240 0.236 0.293
39
Trilemma in the transmission of global risk to capital flows: robustness
Dependent variable: Total capital flows Policy controls: Chinn-Ito de jure index of capital account liberalisation (KAOPEN) and Ilzetzki, Reinhart and Rogoff (IRR) exchange rate regime classification
Notes: The dependent variable is “Total capital inflows””. The model includes country-specific fixed effects, four lags of the dependent variable and a vector of domestic (inflation and GDP growth) and global (GDP growth) control variables that can affect capital flows (omitted for space reasons). The asterisks ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively.
Rubric
www.ecb.europa.eu ©
(1) (2) (3) (4) (5) (6) (7) (8)
Benchmark Advanced economies
Emerging economies
Excl. euro area
Excl. financial centres
Excl. global fin. crisis
Including crises
Including time
dummies
De jure capital account openness (KAOPEN) -0.076 3.948 -0.032 -0.386 -0.203 -0.718 -0.108 0.162(0.667) (3.073) (0.539) (0.662) (0.612) (0.598) (0.701) (0.568)
Strict peg, OST 0.569 1.738 0.512 0.475 0.621 0.596 0.767* 0.653(0.514) (1.522) (0.438) (0.490) (0.419) (0.509) (0.448) (0.514)
Soft peg, OST 0.321 1.186 0.141 0.367 0.179 0.156 0.270 0.444(0.351) (1.166) (0.200) (0.332) (0.220) (0.290) (0.318) (0.281)
US monetary policy surprise -0.080 0.166 -0.402 -0.173 0.235 0.205 -0.234(0.336) (0.533) (0.309) (0.302) (0.295) (0.345) (0.376)
Global Stock Market Factor (GSMF) 1.021*** 3.488* 0.675*** 1.079*** 0.871*** 0.987*** 0.989***(0.276) (2.024) (0.141) (0.247) (0.253) (0.320) (0.263)
GSMF * KAOPEN -1.751*** -3.814* -1.891*** -1.844*** -1.669*** -1.574*** -1.725*** -1.514***(0.375) (2.224) (0.347) (0.362) (0.339) (0.419) (0.358) (0.374)
GSMF * Strict peg, OST -1.415*** -1.188* -1.260*** -1.503*** -1.331*** -1.401*** -1.462*** -1.489***(0.329) (0.667) (0.281) (0.341) (0.329) (0.400) (0.395) (0.393)
GSMF * Soft peg, OST -0.367 -1.390** 0.035 -0.275 -0.139 -0.432 -0.339 -0.419(0.266) (0.646) (0.175) (0.260) (0.192) (0.307) (0.300) (0.253)
Observations 4,343 1,784 2,559 3,715 4,075 4,107 4,727 4,343Countries 50 18 32 50 47 50 50 50R2 0.144 0.102 0.306 0.154 0.158 0.133 0.137 0.190
40
The trilemma in the transmission of global risk to “other investment”
Notes: The dependent variable is “Other investment”. The model includes country-specific fixed effects, four lags of the dependent variable and a vector of domestic (inflation and GDP growth) and global (GDP growth) control variables that can affect capital flows (omitted for space reasons). The asterisks ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively.
Dependent variable: Other investment Policy controls: Chinn-Ito de jure index of capital account liberalisation (KAOPEN) and Obstfeld, Shambaugh and Taylor (OST) exchange rate regime classification
Rubric
www.ecb.europa.eu ©
(1) (2) (3) (4) (5) (6) (7) (8)
Benchmark Advanced economies
Emerging economies
Excl. euro area
Excl. financial centres
Excl. global fin. crisis
Including crises
Including time
dummies
De jure capital account openness (KAOPEN) -0.227 6.318** -0.297 -0.894 -0.246 -0.763 -0.203 0.040(0.643) (3.140) (0.491) (0.654) (0.588) (0.580) (0.672) (0.651)
Strict peg, IRR 2.356*** 4.282*** 2.017** 3.801*** 1.182* 2.272*** 2.053*** 2.685*(0.660) (1.438) (0.778) (0.887) (0.603) (0.721) (0.620) (1.518)
Soft peg, IRR 2.314*** 6.137*** 1.163** 3.165*** 0.845** 2.331*** 1.785** 2.411*(0.741) (2.159) (0.510) (0.781) (0.371) (0.837) (0.751) (1.314)
US monetary policy surprise -0.091 0.130 -0.389 -0.163 0.229 0.211 -0.258(0.340) (0.539) (0.308) (0.308) (0.292) (0.345) (0.381)
Global Stock Market Factor (GSMF) 1.413*** 3.303* 0.868* 1.568*** 1.404*** 1.398*** 1.187***(0.360) (1.834) (0.509) (0.348) (0.311) (0.430) (0.342)
GSMF * KAOPEN -1.939*** -3.723* -1.846*** -2.079*** -1.767*** -1.840*** -1.835*** -1.614***(0.397) (2.034) (0.279) (0.396) (0.320) (0.447) (0.374) (0.403)
GSMF * Strict peg, IRR -1.486*** -0.975 -1.461** -1.768*** -1.609*** -1.394** -1.429** -1.302**(0.502) (0.685) (0.687) (0.609) (0.473) (0.608) (0.554) (0.597)
GSMF * Soft peg, IRR -0.542** -0.749 -0.271 -0.576** -0.690*** -0.579** -0.356 -0.247(0.226) (0.545) (0.524) (0.249) (0.227) (0.257) (0.268) (0.468)
Observations 4,343 1,784 2,559 3,715 4,075 4,107 4,727 4,343Countries 50 18 32 50 47 50 50 50R2 0.144 0.105 0.305 0.156 0.157 0.133 0.137 0.190
41
The trilemma in the transmission of global risk to “other investment”
Notes: The dependent variable is “Other investment”. The model includes country-specific fixed effects, four lags of the dependent variable and a vector of domestic (inflation and GDP growth) and global (GDP growth) control variables that can affect capital flows (omitted for space reasons). The asterisks ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively.
Dependent variable: Other investment Policy controls: Chinn-Ito de jure index of capital account liberalisation (KAOPEN) and Ilzetzki, Reinhart and Rogoff (IRR) exchange rate regime classification